Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method for operating a database and a cache of at least a portion of the database, the method comprising: receiving a plurality of read requests to read a data entity from the database; determining whether each of the plurality of read requests was serviced from the database or from the cache; counting a quantity of the requests serviced from the database and a quantity of the requests serviced from the cache; receiving a write request to alter the data entity in the database; and determining whether to update the cache to reflect the alteration to the data entity in the write request according to the quantity of the requests serviced from the database and the quantity of the requests serviced from the cache; wherein counting the quantity of the requests serviced from the database and the quantity of the requests serviced from the cache is performed over two or more periods of time, wherein the method further comprises: computing, for each of the periods of time, a respective ratio of the quantity of the requests serviced from the database to the quantity of the requests serviced from the cache within that period of time; wherein determining whether to update the cache to reflect the write request is according to the respective ratios for the two or more periods of time.
This invention relates to optimizing cache updates in database systems by dynamically determining whether to propagate write operations to a cache based on historical read request patterns. The problem addressed is inefficient cache management, where unnecessary cache updates can degrade performance by consuming resources without improving read efficiency. The method involves monitoring read requests to a data entity, tracking whether each request is serviced from the database or the cache, and counting the quantities of requests serviced from each source over multiple time periods. For each period, a ratio of database-serviced requests to cache-serviced requests is computed. When a write request is received, the decision to update the cache depends on these ratios across the monitored periods. If the cache is frequently used (i.e., high cache-serviced requests), the cache is updated to reflect the write. If the database is predominantly used (i.e., high database-serviced requests), the cache may be skipped to avoid unnecessary updates. This adaptive approach ensures cache consistency only when beneficial, improving system efficiency by reducing redundant cache operations.
2. The method of claim 1 , wherein the method further comprises: causing the cache to be updated when a ratio of the quantity of the requests serviced from the database to the quantity of the requests serviced from the cache exceeds a predetermined threshold.
This invention relates to database caching systems designed to improve data retrieval efficiency. The problem addressed is the suboptimal performance that occurs when a caching system fails to dynamically adjust to changing access patterns, leading to either excessive cache misses or stale cache data. The invention provides a method for intelligently updating a cache based on real-time performance metrics. The method involves monitoring the ratio of database requests to cache requests. When this ratio exceeds a predetermined threshold, indicating that the cache is no longer effectively servicing requests, the system triggers an update of the cache. This ensures that frequently accessed data remains in the cache, reducing latency and database load. The threshold can be set based on system requirements, such as desired response times or database load limits. The update process may involve invalidating stale entries, refreshing data from the database, or rebalancing cache contents to prioritize high-demand data. By dynamically adjusting the cache based on actual usage patterns, the system maintains optimal performance without manual intervention. This approach is particularly useful in high-traffic environments where data access patterns may fluctuate unpredictably.
3. The method of claim 1 , wherein determining whether to update the cache to reflect the write request according to the quantity of the requests serviced from the database and the quantity of the requests serviced from the cache comprises: applying a predictive algorithm to the quantity of the requests serviced from the database and the quantity of the requests serviced from the cache that calculates a likelihood that a future read request will be serviced from the database.
This invention relates to optimizing cache performance in database systems by dynamically determining whether to update a cache based on historical request patterns. The problem addressed is inefficient cache utilization, where unnecessary updates degrade performance or excessive reliance on the database increases latency. The solution involves analyzing the ratio of requests serviced from the database versus the cache to predict future read request behavior. A predictive algorithm evaluates these quantities to estimate the likelihood that a future read request will require data from the database rather than the cache. If the algorithm determines that database access is probable, the cache is updated to reflect recent write requests, ensuring data consistency. Conversely, if cache hits are frequent, updates may be deferred to reduce overhead. The method dynamically adjusts cache behavior based on real-time request patterns, improving system efficiency by balancing consistency and performance. The predictive algorithm may use statistical models, machine learning, or heuristic approaches to assess request trends and optimize cache updates accordingly. This approach enhances system responsiveness by minimizing unnecessary cache updates while maintaining data accuracy.
4. The method of claim 3 , wherein the predictive algorithm comprises a regression analysis.
A system and method for predictive analysis in data processing involves using a predictive algorithm to forecast outcomes based on input data. The predictive algorithm employs regression analysis to model relationships between variables, enabling accurate predictions. The method includes collecting input data, preprocessing the data to remove noise and inconsistencies, and applying the regression-based predictive algorithm to generate forecasts. The system may also include a user interface for inputting data and displaying results, as well as a data storage component for retaining historical data and model parameters. The regression analysis may utilize linear, polynomial, or other regression techniques to fit a model to the input data, optimizing parameters to minimize prediction errors. The system is designed to handle large datasets efficiently, ensuring real-time or near-real-time predictions. Applications include financial forecasting, risk assessment, and operational optimization in various industries. The method improves decision-making by providing data-driven insights and reducing uncertainty in predictions.
5. The method of claim 3 , wherein the method further comprises: causing the cache to be updated when the likelihood that the future read request will be serviced from the database exceeds a predetermined threshold.
A system and method for optimizing data retrieval in a computing environment involves managing a cache to reduce latency and improve efficiency when accessing a database. The system monitors read requests to determine whether future requests are likely to be serviced from the database rather than the cache. When the likelihood of a future read request being serviced from the database exceeds a predetermined threshold, the cache is updated to ensure that frequently accessed data is available in the cache, reducing the need to fetch data from the slower database. This dynamic updating mechanism helps balance the trade-off between cache storage efficiency and access speed, ensuring that the most relevant data is retained in the cache while minimizing unnecessary updates. The method may involve analyzing historical access patterns, predicting future access trends, and adjusting cache contents accordingly to optimize performance. By dynamically updating the cache based on predicted access patterns, the system reduces latency and improves overall system efficiency.
6. A system for operating a database and a cache of at least a portion of the database, the system comprising: a cache management system configured to be in electronic communication with the database and with the cache, the cache management system comprising a processor and a computer-readable memory storing instructions that, when executed by the processor, cause the cache management system to: receive a plurality of read requests to read a data entity from the database; determine whether each of the plurality of read requests was serviced from the database or from the cache; count a quantity of the requests serviced from the database and a quantity of the requests serviced from the cache; receive a write request to alter the data entity in the database; and determine whether to update the cache to reflect the alteration to the data entity in the write request according to the quantity of the requests serviced from the database and the quantity of the requests serviced from the cache; wherein counting the quantity of the requests serviced from the database and the quantity of the requests serviced from the cache is performed over two or more periods of time, wherein the memory stores further instructions that, when executed by the processor, cause the cache management system to: compute, for each of the periods of time, a respective ratio of the quantity of the requests serviced from the database to the quantity of the requests serviced from the cache within that period of time; wherein determining whether to update the cache to reflect the write request is according to the respective ratios for the two or more periods of time.
A system operates a database and a cache storing a portion of the database. The system includes a cache management system that monitors read and write operations to optimize cache updates. The cache management system tracks read requests for a data entity, determining whether each request is serviced from the database or the cache. It counts the number of requests serviced from each source over multiple time periods and calculates a ratio of database-serviced requests to cache-serviced requests for each period. When a write request alters the data entity, the system decides whether to update the cache based on these ratios. The decision considers historical read patterns to balance cache consistency with performance. This approach ensures the cache is updated only when necessary, reducing unnecessary updates while maintaining data accuracy. The system dynamically adjusts cache behavior based on access patterns, improving efficiency in database operations.
7. The system of claim 6 , further comprising the database.
A system for managing and analyzing data includes a processing unit configured to receive input data from one or more sources, a memory unit storing executable instructions for the processing unit, and a user interface for displaying results. The system further includes a database for storing the input data, processed data, and analysis results. The processing unit is configured to perform data processing tasks such as filtering, transformation, and aggregation based on predefined rules or user inputs. The user interface allows users to interact with the system, input parameters, and visualize the processed data. The database ensures persistent storage and retrieval of data, enabling historical analysis and trend tracking. The system may also include communication interfaces to connect with external data sources or other systems, facilitating data exchange and integration. The overall system is designed to streamline data workflows, improve efficiency, and provide actionable insights from large datasets.
8. The system of claim 6 , further comprising the cache.
A system for managing data storage and retrieval in a computing environment addresses the problem of inefficient data access, particularly in scenarios where frequently accessed data is not optimally cached, leading to performance bottlenecks. The system includes a primary storage device for storing data and a secondary storage device for temporarily storing frequently accessed data to reduce latency. The system further includes a cache, which is a high-speed memory component that stores a subset of data from the primary storage device to further accelerate data retrieval. The cache operates in conjunction with the secondary storage device to ensure that the most frequently accessed data is readily available, minimizing the need to access the slower primary storage device. The system dynamically monitors data access patterns to determine which data should be stored in the cache, optimizing performance based on usage trends. This hierarchical storage approach ensures that data is retrieved efficiently, reducing latency and improving overall system responsiveness. The cache may be implemented using various high-speed memory technologies, such as solid-state drives or random-access memory, depending on the specific requirements of the application. The system is particularly useful in environments where rapid data access is critical, such as in database management systems, web servers, or real-time analytics platforms. By intelligently managing data placement across different storage tiers, the system enhances performance while maintaining cost-effectiveness.
9. The system of claim 6 , wherein the instructions, when executed by the processor, further cause the cache management system to: cause the cache to be updated when a ratio of the quantity of the requests serviced from the database to the quantity of the requests serviced from the cache exceeds a predetermined threshold.
This invention relates to a cache management system for optimizing data retrieval in a database environment. The system addresses the problem of inefficient data access, where frequent database queries degrade performance due to high latency and resource consumption. The solution involves dynamically managing a cache to balance between cache hits and database access, ensuring optimal system performance. The cache management system monitors the ratio of requests serviced from the database versus those serviced from the cache. When this ratio exceeds a predetermined threshold, indicating excessive database access, the system triggers an update to the cache. This update may involve preloading frequently accessed data or adjusting cache policies to prioritize certain queries. The system ensures that the cache remains effective by dynamically adapting to changing access patterns, reducing database load, and improving response times. The invention also includes a processor executing instructions to perform these operations, ensuring real-time adjustments based on system performance metrics. The cache management system may integrate with existing database architectures, making it adaptable to various applications requiring efficient data retrieval. By dynamically updating the cache based on access ratios, the system minimizes unnecessary database queries, enhancing overall system efficiency and scalability.
10. The system of claim 6 , wherein determining whether to update the cache to reflect the write request according to the quantity of the requests serviced from the database and the quantity of the requests serviced from the cache comprises: applying a predictive algorithm to the quantity of the requests serviced from the database and the quantity of the requests serviced from the cache that calculates a likelihood that a future read request will be serviced from the database.
A system for optimizing cache performance in database environments improves data retrieval efficiency by dynamically adjusting cache updates based on request patterns. The system monitors the quantity of requests serviced from the database and the cache, then uses this data to determine whether to update the cache in response to write requests. A predictive algorithm analyzes these quantities to calculate the likelihood that future read requests will be serviced from the database rather than the cache. If the likelihood exceeds a threshold, the system may suppress cache updates for certain write requests to reduce unnecessary cache invalidations or updates, thereby improving overall system performance. The predictive algorithm may employ statistical models, machine learning techniques, or other analytical methods to assess request patterns and make data-driven decisions. This approach ensures that cache resources are allocated efficiently, balancing between maintaining up-to-date data and minimizing overhead from frequent cache updates. The system is particularly useful in high-throughput environments where minimizing latency and optimizing resource usage are critical.
11. The system of claim 10 , wherein the predictive algorithm comprises a regression analysis.
A system for predictive analysis in a technical domain, such as data processing or machine learning, addresses the challenge of accurately forecasting outcomes based on input data. The system includes a predictive algorithm designed to process input data and generate predictions. The algorithm employs regression analysis, a statistical method that models relationships between variables to estimate future values. Regression analysis helps identify patterns and trends in the data, enabling the system to make informed predictions. The system may also include data preprocessing components to clean, normalize, or transform input data before analysis, ensuring higher accuracy in the predictive model. Additionally, the system may incorporate feedback mechanisms to refine the predictive algorithm over time, improving its performance with continuous use. The regression analysis within the predictive algorithm may utilize linear, polynomial, or other regression techniques depending on the data characteristics and the specific application. This approach enhances decision-making by providing reliable forecasts based on historical and real-time data.
12. The system of claim 10 , wherein the instructions, when executed by the processor, further cause the cache management system to: cause the cache to be updated when the likelihood that the future read request will be serviced from the database exceeds a predetermined threshold.
The system relates to cache management in database systems, specifically addressing the challenge of efficiently updating cache contents to improve read performance. The system includes a cache management system that monitors and evaluates the likelihood that future read requests will be serviced from the database rather than the cache. When this likelihood exceeds a predetermined threshold, the cache is updated to ensure that frequently accessed data is retained, reducing latency and improving overall system performance. The cache management system dynamically adjusts cache updates based on predictive analytics, optimizing resource usage and minimizing unnecessary cache operations. This approach enhances efficiency by prioritizing data that is more likely to be requested, reducing the need for repeated database access and improving response times for read operations. The system integrates with existing database infrastructure, ensuring seamless operation while dynamically adapting to changing access patterns. By intelligently managing cache updates, the system reduces computational overhead and improves scalability, making it suitable for high-performance database environments.
13. The system of claim 6 , wherein determining whether to update the cache to reflect the write request according to the quantity of the requests serviced from the database and the quantity of the requests serviced from the cache comprises determining whether to update the cache to reflect the write request according to the quantity of the requests serviced from the database on two or more specified days in the past and the quantity of the requests serviced from the cache on the two or more specified days in the past.
A system for managing cache updates in a database environment addresses the challenge of efficiently maintaining cache consistency while minimizing performance overhead. The system monitors request traffic to determine whether to update a cache in response to write operations. Specifically, it evaluates the quantity of requests serviced from the database and the quantity serviced from the cache over multiple past days. By analyzing historical request patterns, the system decides whether to propagate write changes to the cache, ensuring that cache updates align with actual usage trends. This approach reduces unnecessary cache invalidations or updates, improving system efficiency and responsiveness. The system dynamically adjusts cache behavior based on historical data, optimizing performance for workloads with varying access patterns. The solution is particularly useful in environments where read-heavy workloads dominate, as it avoids excessive cache updates while maintaining data consistency. The system's decision-making process relies on aggregated request metrics from multiple past days, providing a more stable and reliable basis for cache management compared to short-term or instantaneous metrics. This method ensures that cache updates are aligned with long-term usage patterns, reducing the risk of performance degradation due to frequent cache updates.
14. A system for operating a database, the system comprising: a cache of at least a portion of the database; and a cache management system configured to be in electronic communication with the database and with the cache, the cache management system comprising a processor and a computer-readable memory storing instructions that, when executed by the processor, cause the cache management system to: receive a plurality of read requests to read a data entity from the database; for each of the plurality of read requests: determine if the cache has an accurate copy of the data entity; responsive to determining that the cache has an accurate copy of the data entity, service the request from the cache; and responsive to not determining that the cache has an accurate copy of the data entity, service the request from the database; count a quantity of the requests serviced from the database and a quantity of the requests serviced from the cache; receive a write request to alter the data entity in the database; and determine whether to update the cache to reflect the alteration to the data entity in the write request according to the quantity of the requests serviced from the database and the quantity of the requests serviced from the cache; wherein counting the quantity of the requests serviced from the database and the quantity of the requests serviced from the cache is performed over two or more periods of time, wherein the memory stores further instructions that, when executed by the processor, cause the cache management system to: compute, for each of the periods of time, a respective ratio of the quantity of the requests serviced from the database to the quantity of the requests serviced from the cache within that period of time; wherein determining whether to update the cache to reflect the write request is according to the respective ratios for the two or more periods of time.
The system operates in the domain of database management, specifically addressing the challenge of efficiently maintaining cache consistency in database systems. The system includes a cache storing at least a portion of the database and a cache management system that communicates with both the cache and the database. The cache management system processes read requests by first checking if the cache contains an accurate copy of the requested data entity. If the cache has an accurate copy, the request is serviced from the cache; otherwise, it is serviced from the database. The system tracks the number of requests serviced from the database and the cache over multiple time periods, calculating a ratio of database-serviced requests to cache-serviced requests for each period. When a write request is received to modify a data entity, the system determines whether to update the cache based on these ratios. This approach optimizes cache updates by dynamically assessing access patterns, reducing unnecessary cache invalidations and improving performance. The system ensures that cache updates are performed only when justified by historical access trends, balancing consistency with efficiency.
15. The system of claim 14 , further comprising the database.
A system for managing and analyzing data includes a processing unit configured to receive input data from one or more sources, a memory unit storing executable instructions, and a database. The processing unit executes the instructions to process the input data, generate output data, and store the output data in the database. The system may also include a user interface for displaying the output data and receiving user inputs to modify the processing parameters. The database is structured to store the input data, output data, and metadata associated with the data processing operations. The system may further include a communication interface for transmitting the output data to external devices or systems. The processing unit may apply machine learning algorithms to analyze the input data and generate predictive models, which are stored in the database for future reference. The system is designed to handle large-scale data processing tasks efficiently, ensuring data integrity and security throughout the operations. The database may be optimized for fast retrieval and storage of structured and unstructured data, supporting various query types to facilitate data analysis and reporting. The system may also include a security module to enforce access controls and encryption protocols, ensuring that sensitive data is protected. The overall architecture allows for scalability, enabling the system to adapt to increasing data volumes and processing demands.
16. The system of claim 14 , wherein determining whether to update the cache to reflect the write request according to the quantity of the requests serviced from the database and the quantity of the requests serviced from the cache comprises: applying a predictive algorithm to the quantity of the requests serviced from the database and the quantity of the requests serviced from the cache that calculates a likelihood that a future read request will be serviced from the database.
In database systems, caching is used to improve performance by storing frequently accessed data in a faster-access memory layer. However, maintaining cache consistency with the underlying database is challenging, especially when write operations occur. If the cache is updated too aggressively, it may waste resources on infrequently accessed data. If it is updated too conservatively, read requests may miss cached data, reducing performance benefits. This invention improves cache management by dynamically determining whether to update the cache based on historical request patterns. The system tracks the quantity of requests serviced from the database and the quantity serviced from the cache. A predictive algorithm analyzes these quantities to calculate the likelihood that a future read request will be serviced from the database. If the likelihood is high, the cache is updated to reflect the write request, ensuring consistency and improving future read performance. If the likelihood is low, the cache may be left unchanged to avoid unnecessary updates. The predictive algorithm may use statistical models, machine learning, or other techniques to assess request patterns and optimize cache updates. This approach balances cache consistency with resource efficiency, enhancing overall system performance.
17. The system of claim 16 , wherein the instructions, when executed by the processor, further cause the cache management system to: update the cache when the likelihood that the future read request will be serviced from the database exceeds a predetermined threshold.
This invention relates to a cache management system for optimizing database performance by dynamically updating a cache based on predictive analytics. The system addresses the problem of inefficient cache utilization, where frequently accessed data is not retained, leading to redundant database queries and degraded performance. The system includes a processor and a memory storing instructions that, when executed, enable the cache management system to predict the likelihood that a future read request will be serviced from the database rather than the cache. This prediction is based on analyzing historical access patterns, query frequency, and other relevant metrics. The system further updates the cache when the predicted likelihood exceeds a predetermined threshold, ensuring that high-probability future requests are serviced from the cache, reducing database load and improving response times. The cache management system may also monitor cache performance metrics, such as hit rates and latency, to refine its predictive model over time. By dynamically adjusting cache content based on predictive analytics, the system enhances efficiency and reduces the computational overhead associated with unnecessary database queries.
18. The system of claim 16 , wherein the instructions, when executed by the processor, further cause the cache management system to: update the cache when a ratio of the quantity of the requests serviced from the database to the quantity of the requests serviced from the cache exceeds a predetermined threshold.
This invention relates to a cache management system for optimizing data retrieval in a database environment. The system addresses the problem of inefficient data access, where frequent database queries can lead to performance bottlenecks and increased latency. The invention improves upon prior art by dynamically adjusting cache behavior based on real-time performance metrics. The cache management system monitors the ratio of requests serviced from the database versus those serviced from the cache. When this ratio exceeds a predetermined threshold, indicating that the cache is underutilized, the system triggers an update to the cache. This update may involve refreshing stale data, expanding the cache size, or adjusting caching policies to better align with current access patterns. The system ensures that the cache remains effective by dynamically responding to changes in data access behavior, thereby reducing unnecessary database queries and improving overall system performance. The invention is particularly useful in high-traffic environments where efficient data retrieval is critical.
Unknown
December 15, 2020
Browse 5M+ US patents with plain-English claim translations and AI-generated analysis.